Server Quality Checklist

Tool Scores

• json_skeletonA
  4.2/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the tool creates a transformed version of JSON files (preserving structure while truncating values and deduplicating arrays), addresses size constraints, and mentions the specific error scenario it helps resolve. It doesn't cover all potential behavioral aspects like error handling or performance characteristics, but provides substantial operational context beyond basic functionality.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is perfectly concise with two sentences that each serve distinct purposes: the first explains what the tool does and its key features, the second provides the specific usage context. There's zero wasted language, and the most important information (what it creates and why) is front-loaded. Every word earns its place.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description provides good contextual completeness. It explains the tool's purpose, when to use it, and key behavioral characteristics. The main gap is the lack of information about the output format - what exactly the 'JSON skeleton' looks like, whether it maintains the original file structure completely, or if there are any limitations on the transformations. However, for a tool with good schema coverage and clear purpose, it's mostly complete.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema - it doesn't explain how 'max_length' relates to 'truncated values' or how 'type_only' affects the deduplication process. However, it provides overall context about what the parameters collectively achieve, which maintains the baseline score.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose with specific verbs ('create', 'preserves', 'truncated', 'deduplicated') and resources ('JSON skeleton', 'large JSON files'). It distinguishes itself by addressing a specific error scenario ('File content exceeds maximum allowed size') and explains what makes the output 'lightweight' - truncated values and deduplicated arrays. This goes beyond just restating the name/title.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides clear context for when to use this tool: 'when encountering File content exceeds maximum allowed size errors with large JSON files.' This gives a specific trigger condition. However, it doesn't mention when NOT to use it or discuss alternatives (though there are no sibling tools listed, so this limitation is understandable). The guidance is explicit but lacks exclusion criteria.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.